Closed-loop Artificial Pancreas: Algorithm Engineering and Clinical Evaluation

描述(由申请人提供)：这项提案寻求建立在一系列有希望的研究基础上，这些研究已经产生了一种闭环式人工胰腺(AP)的工作原型，该原型通过控制算法将连续的葡萄糖传感与自动胰岛素输送相结合。AP由三部分组成：连续血糖传感器、连续皮下胰岛素输注泵和人工胰腺软件(APS)。APS正处于美国食品和药物管理局(FDA)用于全自动闭环对照临床试验的最后审查阶段(主文件MAF-1625)。具体目标是：1)开发人工胰腺，以优化胰岛素的输送，并将与饮食有关的血糖漂移降至最低；2)扩展人工胰腺，以包括胰岛素敏感性的变化和个体差异；以及3)进一步开发使用多参数模型预测控制(MpMPC)的算法，以减少在线计算，开发有效的在线监控策略，以确保AP正常运行，并支持多输入系统。为了实现我们的总体目标，即实现胰岛素输送的全自动闭环装置，我们将采用阶段性方法，其中临床研究也采用并行工程设计方法，以完善我们的AP。在硅胶测试和人体临床测试中，将用于验证模型开发的每一步。这一系列研究的最终目标是一种功能性AP，它将通过受控的胰岛素输送提供全天候的血糖调节，以响应检测到的血糖水平变化模式，以便在1型糖尿病患者中实现最佳的血糖调节。在为随后的胰岛素注射设定限制时，将特别考虑先前输注的潜在可用胰岛素的量(机载胰岛素)。该提案描述了用于血糖调节的多参数模型预测控制方法，以及在过夜、饮食和锻炼条件下对AP的广泛的计算机和临床验证。该应用程序源于加州大学圣巴巴拉分校(UCSB)的系统工程师与位于不到10英里之外的著名的Sansum糖尿病研究所(Sansum)专门从事糖尿病研究的研究医生之间的长期合作。这个团队作为人工胰腺文献的主要贡献者和糖尿病技术的国际领导者而脱颖而出。 与公众健康相关：该项目旨在开发一种功能性人工胰腺，它将通过受控的胰岛素输送来响应检测到的血糖水平变化模式，提供全天候的血糖调节，以便在1型糖尿病患者中实现最佳的血糖调节。在为随后的胰岛素注射设定限制时，将特别考虑先前输注的潜在可用胰岛素的量(机载胰岛素)。该提案描述了用于血糖调节的多参数模型预测控制方法，以及在过夜、饮食和锻炼条件下对AP的广泛的计算机和临床验证。

DESCRIPTION (provided by applicant): This proposal seeks to build on a promising line of research that has already resulted in a working prototype of a closed-loop artificial pancreas (AP) that combines continuous glucose sensing with automated insulin delivery via a control algorithm. The AP consists of three components: a continuous glucose sensor, a continuous subcutaneous insulin infusion pump, and artificial pancreas software (APS). The APS is in the final stages of review by the Food and Drug Administration for use in fully automated closed-loop control clinical trials (Master File MAF-1625 ). The specific aims are: 1) Development of the Artificial Pancreas to optimize insulin delivery and minimize meal-related excursions in glucose, 2) Expansion of the Artificial Pancreas to include alterations and individual differences in insulin sensitivity, and 3) Further development of the algorithms using multi-parametric model predictive control (mpMPC) in order to reduce online computation, develop effective online monitoring strategies to ensure that the AP is operating properly, and accommodate multiple input systems. In the quest to achieve our overall goal of a completely automated closed-loop device for insulin delivery, we will utilize a staged approach in which the clinical studies also have a concurrent engineering design approach in order to refine our AP. In silico testing and human in-clinic testing will be used to validate each step of model development. The ultimate goal of this line of research is a functional AP that will provide around-the-clock glucose regulation through controlled insulin delivery in response to detected patterns of changes in glucose levels in order to achieve optimal glucose regulation in subjects with type 1 diabetes. Special consideration will be given to the amount of potentially available insulin from prior infusions (insulin-on-board) in setting constraints for subsequent insulin delivery. The proposal describes multi-parametric model predictive control approaches to glycemic regulation and extensive in silico and clinical validation of the AP under overnight, meal, and exercise conditions. This application grows out of a long-standing collaboration between systems engineers at the University of California, Santa Barbara (UCSB) and research physicians specializing in diabetes research at the prestigious Sansum Diabetes Research Institute (Sansum) located less than ten miles away. This team has distinguished itself as a major contributor to the artificial pancreas literature and as an international leader in diabetes technology. PUBLIC HEALTH RELEVANCE: This project aims to develop a functional artificial pancreas that will provide around-the-clock glucose regulation through controlled insulin delivery in response to detected patterns of changes in glucose levels in order to achieve optimal glucose regulation in subjects with type 1 diabetes. Special consideration will be given to the amount of potentially available insulin from prior infusions (insulin-on-board) in setting constraints for subsequent insulin delivery. The proposal describes multi-parametric model predictive control approaches to glycemic regulation and extensive in silico and clinical validation of the AP under overnight, meal, and exercise conditions.